The metering of audio/video content (e.g., television programs, radio programs, etc.) is typically performed by collecting consumption records (e.g., viewing records) or other consumption information from a group of statistically selected households. These viewing records are typically generated by identifying the audio/video content displayed in these households.
Some techniques for identifying displayed audio/video content are based on the use of audio and/or video signatures. In general, signature-based audio/video content identification techniques use one or more characteristics of presented (but not yet identified) audio/video content to generate a substantially unique signature (e.g., a series of digital values, a waveform, etc.) for that content. The signature information for the content being presented or rendered is then typically compared to signature information generated for known audio/video content. When a substantial match is found, the audio/video content can, with a relatively high probability, be identified as the known audio/video content having substantially matching signature information.
Although the use of signatures to identify consumed audio/video content is growing, known computationally efficient signature-based program identification techniques are not sufficiently reliable because these known techniques typically ignore important distinguishing characteristics of the audio/video signal. As a result, such known techniques may limit or prevent the identification of audio/video content and/or may result in an incorrect identification of that content.